التفاصيل البيبلوغرافية
العنوان: |
Bayes beyond the predictive distribution. |
المؤلفون: |
Székely A; Department of Computational Sciences, HUN-REN Wigner Research Centre for Physics, Budapest, Hungary szekely.anna@wigner.hu orban.gergo@wigner.mta.huhttp://golab.wigner.mta.hu/people/anna-szekely/http://golab.wigner.mta.hu/people/gergo-orban/.; Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary., Orbán G; Department of Computational Sciences, HUN-REN Wigner Research Centre for Physics, Budapest, Hungary szekely.anna@wigner.hu orban.gergo@wigner.mta.huhttp://golab.wigner.mta.hu/people/anna-szekely/http://golab.wigner.mta.hu/people/gergo-orban/. |
المصدر: |
The Behavioral and brain sciences [Behav Brain Sci] 2024 Sep 23; Vol. 47, pp. e166. Date of Electronic Publication: 2024 Sep 23. |
نوع المنشور: |
Journal Article |
اللغة: |
English |
بيانات الدورية: |
Publisher: Cambridge Univ. Press Country of Publication: England NLM ID: 7808666 Publication Model: Electronic Cited Medium: Internet ISSN: 1469-1825 (Electronic) Linking ISSN: 0140525X NLM ISO Abbreviation: Behav Brain Sci Subsets: MEDLINE |
أسماء مطبوعة: |
Original Publication: Cambridge [Eng.], New York, Cambridge Univ. Press. |
مواضيع طبية MeSH: |
Bayes Theorem* , Cognition*/physiology, Humans ; Learning/physiology ; Models, Psychological |
مستخلص: |
Binz et al. argue that meta-learned models offer a new paradigm to study human cognition. Meta-learned models are proposed as alternatives to Bayesian models based on their capability to learn identical posterior predictive distributions. In our commentary, we highlight several arguments that reach beyond a predictive distribution-based comparison, offering new perspectives to evaluate the advantages of these modeling paradigms. |
تواريخ الأحداث: |
Date Created: 20240923 Date Completed: 20240923 Latest Revision: 20240923 |
رمز التحديث: |
20240923 |
DOI: |
10.1017/S0140525X24000086 |
PMID: |
39311517 |
قاعدة البيانات: |
MEDLINE |